To address the limitations currently experienced regarding the comprehensiveness and effectiveness of online learning evaluation in the smart education context, this paper proposes a novel framework for assessing online learning behavior based on the fuzzy analytic hierarchy process(FAHP) and the fuzzy synthetic evaluation method(FSEM). Drawing upon the CIPP(context, input, process, product) educational evaluation model and integrating the educational evaluation tag taxonomy system, the framework identifies five key dimensions: learning exploration, programming practice, knowledge acquisition, collaborative innovation, and communication interaction. These dimensions are further delineated into secondary and tertiary indicators to ensure comprehensive evaluation coverage. The framework utilizes FAHP-FSEM to determine the weights of each indicator level and employs consistency testing to validate the scientific and rational nature of the evaluation process. Implemented on the Shuishan Online platform, the framework leverages extensive multi-source process learning data to facilitate comprehensive evaluation from multiple perspectives and across various dimensions. Student profiles and learning behavior patterns are presented via a visual dashboard. This framework provides robust data support for enhancing personalized learning outcomes and advancing educational reform, demonstrating its broad applicability and potential.